The variation of soil organic carbon (SOC) spatial distribution is dependent on the relative contributions of different environmental factors, and the dominant factors change according to study scales. Here, geostatistical and remote sensing techniques were used to gain deep knowledge about SOC spatial distribution patterns and their dominant determinants at different study scales; specifically, the structure of the spatial variability of SOC content at the county, regional, and watershed scales in Aohan, China were analyzed. The results show that altitude and normalized difference vegetation index (NDVI) are the key predictors explaining 49.6% of the SOC variability at the county scale; NDVI and slope are the key predictors explaining 36.2% of the SOC variability at the regional scale; and terrain factors are the most significant factors at the watershed scale. These three scales have a moderate spatial correlation in terms of SOC content. As the study scale widens, the spatial variability attributable to the random factors increases gradually, whereas the variability attributable to the structural factors gradually weakens. Soil type and land use type are the key factors influencing the SOC content at these three scales. At all scales, the SOC contents of the different land use types differ significantly in the order forestland > shrubland > grassland. Conservation of regional soil and water and prevention of soil desertification are effective measures for improving SOC content.

Plant ecological niche characteristics are powerful representations of plant survival status. Understory herbaceous species in plantation forests are sensitive to local ecological environment changes; patterns of ecological niche changes of herbaceous plants under plantation forests are of great significance for maintaining the stability and sustainable development of plantation forest ecosystems. This study aims to explore the ecological niche characteristics of understory herbaceous species in plantation forests and their influencing factors. Six different site types of Pinus tabulaeformis plantations were selected from a stable plantation community in the feldspathic sandstone area of the Loess Plateau (China). The relative importance value and niche breadth were used as comprehensive quantitative indices to characterize the status, role, and degree of dominance of understory herbaceous species in plantation forests. We found few dominant species of understory herbaceous species in plantation forests, mostly companion species. The niche characteristics of understory herbaceous species in plantation forests varied significantly. For understory herbaceous species, the niche width was positively correlated with slopes and the niche overlap of the sunny slopes was positively relevant with slopes, while that of the shady slopes was negatively correlated. A canonical correspondence analysis indicated that several major factors influencing the niche breadth and niche overlap of understory herbaceous species in plantation forests were different. The canopy density and slope of plantation played a major role in the niche breadth and niche overlap of understory herbaceous species in plantation forests. In summary, the species distribution of understory herbaceous species in plantation forests was determined by site type. The canopy density and geographical slope were the dominant environmental factors for different ecological niche characteristics of understory herbaceous species. The ecological niche variation of different herbaceous species was the consequence of the integrated effects of the plantation and geographical environment.

Variation patterns in plant functional traits and their interrelationships play a crucial role in understanding species coexistence mechanisms and ecological differentiation within local plant communities. However, the dynamic patterns of plant functional traits across different forest successional stages remain insufficiently understood. Here, we investigated the woody species composition of subtropical evergreen–deciduous broadleaved mixed forest across 75 plots, representing three successional stages (20-year-old secondary forest, 35-year-old secondary forest, and old-growth forest (>80 years)), in Xingdoushan and Mulinzi National Nature Reserves, Hubei Province, Central China. We measured four functional traits of woody plants: leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), and wood density (WD). For each different age plant community, we calculated (1) species abundance-weighted mean community trait values, and (2) species-level mean trait values. We applied trait gradient analysis to partition and assess correlations of four functional traits across communities of different successional stages, separating within-community (α components) and between-community (β components) variation. To quantify the extent to which environmental constraints influence trait expression, we used the ecological constraint index (C_i). The results revealed significant variation in the four functional traits across communities at different successional stages. Community-level mean LA and SLA decreased significantly with age, WD increased significantly with age, and there was no significant relationship between LDMC and age. The α trait components consistently varied more widely than β components at different successional stages, indicating that biological competition dominates the assembly of local forest communities across various successional stages. Correlations between the four functional traits were dynamically adjusted with the study scale (community-level and species-level) and forest age. The ecological constraints on the four functional traits varied significantly across forest successional stages, with SLA being subject to the strongest constraints. Our findings reveal that biotic competition predominantly shapes community assembly during the succession of subtropical evergreen–deciduous broadleaved mixed forests, while stronger ecological filtering in old-growth stands underscores their role in maintaining ecosystem stability. These insights support more effective conservation and restoration strategies.